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bokeh python

4.2
(12)

Bokeh is an interactive visualization library for Python that enables beautiful and meaningful visual presentation of data in modern web browsers. With Bokeh, you can quickly and easily create interactive plots, dashboards, and data applications.

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bokeh python review by Clare S.
Clare S.
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"Love using bokeh for interactive plots"

What do you like best?

I like how there are a several pre made interactive plot templates that allow you to generate interactive plots in one line of code, but that there is also room for customization beyond that. It's pretty easy to get started with bokeh to make simple yet useful interactive plots and web pages.

What do you dislike?

I've had some issues getting certain features to work that I've ended up just giving up on. There's a learning curve when trying to make very custom things, without a lot of documentation. It's also difficult to debug and requires learning some javascript, which is useful but increases the learning curve.

Recommendations to others considering the product

I'd recommend this package to users.

What business problems are you solving with the product? What benefits have you realized?

I use Bokeh to make interactive plots for my team at work to use. We use these to monitor the health of the scientific instrument we work on and it's useful to have these over static plots. The screen shot I attached it part of an interactive web page I made with bokeh that allows you to filter data from out instrument from a specific subset to display, and then to download a table.

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bokeh python review by Udhav S.
Udhav S.
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"All the things can be done regarding visualization using Bokeh"

What do you like best?

Bokeh is an interactive visualization library that targets modern web browsers for presentation. Its goal is to provide elegant, concise construction of versatile graphics, and to extend this capability with high-performance interactivity over very large or streaming datasets.

Bokeh can help anyone who would like to quickly and easily create interactive plots, dashboards and data application.

What do you dislike?

As Bokeh is highly interactive visualizing library, obvious its work is good. Because of this its complexity is low. Or its building speed is slow as compared to some other interactive visualizing library.

Recommendations to others considering the product

There is no point not to use Bokeh expect its slower builder quality. So for using it, in different versions of Bokeh function is differently defined to make good presentation, so keep in mind this point if you change any version in your machine.

What business problems are you solving with the product? What benefits have you realized?

Our most of work needs highly graphical data. So that our team members uses photoshop for visualization purpose. But now Bokeh gives what exactly gives photoshop, just by calling any function for particular requirement thing.

What Python Package solution do you use?

Thanks for letting us know!
bokeh python review by Deep K.
Deep K.
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"Plotting with basic glyphs using Bokeh"

What do you like best?

In graph we have to plot many things, to show the presentation of your respected task.

For marking a circle on the graph use the figure class, in which circle() method is there to plot a circle on graph. To use the square to presenting something on graph use its square() method. And many other methods are also available like asterisk(), dash(), diamond(), etc.

What do you dislike?

There certain point why not to use Bokeh? And also there is one point why use Bokeh? Because its complexity is slower in comparison to other frameworks which can do the same task that Bokeh do. But the result we get from its output is too good.

Recommendations to others considering the product

Go through the documentation part from its official website for the plotting of shapes and its methods.

What business problems are you solving with the product? What benefits have you realized?

Annotations can be done easily using Bokeh in case of showing some part of the biomedical generated images. Before we did it manually, but now using Bokeh is too good.

bokeh python review by Priya D.
Priya D.
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"Data visualization with Bokeh"

What do you like best?

Python is THE go-to programming language for any machine leaning, data science part, and bokeh makes it better. It gives us the visual of any particular data that go beyond the capabilities of any other framework.

What do you dislike?

Compare to the other frameworks who do the same job as bokeh do, bokeh is slow to build the things like data visualization or viz. one piece at a time. But on the other side besides of its complexity its end product is good.

Recommendations to others considering the product

Use this under product when you have small assigned work and where complexity is not concerned. But don’t use their where your assigned work is large in amount. Because it take long time to accomplish task.

What business problems are you solving with the product? What benefits have you realized?

Before bokeh framework, our team used to use other framework for such a thing with some different platforms rather than python using bokeh. But when we start using bokeh we get our product is good and feedback from our clients is also becoming good.

bokeh python review by Paolo D.
Paolo D.
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"A picture is worth a thousand words, a good graph is worth even more"

What do you like best?

With bokeh, I can create interactive graphs which gave a whole new dimension to my performance testing reports. Not only they look beautiful, but they let me illustrate concepts in an interactive way, without generating different graphs which are only zoomed in versions or simple numbers: I can show the numbers by hovering over the generated graph instead

What do you dislike?

it took me a while to get the right configuration. Matplotlib works almost out of the box, bokeh takes very little to produce a nice graph, but quite some work to get exactly what you want. Anyway, this is justified by the fact the final outcome is more captivating than Matplotlib and interactive

Recommendations to others considering the product

Watch out for the NumPy dependency: it might be tricky to install on some OS.

Apart from this, installation was smooth and the learning curve shallow enough to start producing logs within the first few minutes of usage

What business problems are you solving with the product? What benefits have you realized?

I managed to automate the full performance testing process by replacing the old tool we were using. I don't need to rely anymore on a black box third party, which produced only certain graphs, I can customize the output I want and format them in a more intelligible way

In addition, inspection for individual results (over millions of samples) is much easier

bokeh python review by Lisa S.
Lisa S.
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"Best way to plot the data"

What do you like best?

Bokeh in python provides you the best interface to create graphs and other charts using inbuilt functions of library which can directly be directly used as a webpage in your webservice.The interactivity's provided by this library is far better then any other plotting library for python.I tried all other libraries like plotly and matplotlib but found this far more better and intuitive.

What do you dislike?

Actually it is very good library to use so nothing to dislike.

Recommendations to others considering the product

Definitely a library worth using for plotting data in more interactive way using python.Because to show something that has been developed, you need some efficient and smart solutions to show them and for that bokeh stands out and is best library used for plotting data and providing good interactions.

What business problems are you solving with the product? What benefits have you realized?

After comparing various libraries for chart and plots finally I came across bokeh and found it easy to use and deploy and so I use bokeh for plotting graphs for our webservice and it directly generates webpage which can be embedded into our existing service.

bokeh python review by User
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"Data visualization library"

What do you like best?

Bokeh allows me and my team to visualize data and information in a way that previously wasnt possible with the cluncky BI tools that we used to use. I think what I love best about bokeh is how easy it is to install and use because it's open source.

What do you dislike?

With open source comes the issue with support. There isn't much support available besides a developer guide which is available on their website so you better have a team of engineers ready to dive deep.

Recommendations to others considering the product

This is a great library to test and use. The documentation is clear and understandable if you have a development team. All in all, good library to try out

What business problems are you solving with the product? What benefits have you realized?

The business problems solved with bokeh are varied. The benefits that I have realized is the ability to visualize data using advanced statistical methods that tools like Tableau and IBM Cognos simply cannot.

bokeh python review by User
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"Bokeh: Great interactive, simple visualizations. Nearly as good as plotly "

What do you like best?

I like that it's fairly easy to create dynamic html visualizations that look slick and feel good. Since I learned R before python for statistics and visualizations, I definitely prefer R's ggplot2 syntax (which plotly can then easily convert to an html version with plotly::ggplotly()). However, for the python work that I do (when my coworkers prefer python notebooks, etc.) the capability of bokeh is great! The api is fairly consistent across different types of plots which is great.

What do you dislike?

While bokeh is pretty strong for creating pretty slice visualizations, I find it more difficult to customize plot themes and features as compared to some other visualization libraries. However, I also find myself more impressed with the default settings of any bokeh plot.

Recommendations to others considering the product

Static visualizations, probably start with seaborn (don't use matplotlib unless you know what you're doing).

Dynamic visualizations, definitely learn bokeh, maybe also plotly

What business problems are you solving with the product? What benefits have you realized?

We typically use bokeh as an open source way of quickly visualizing a new dataset in several ways that we can than share an internal URL or flat html page with other coworkers or management. The ability to send off an html file to some other person and allow them to explore the data easily makes my job a lot more self-serve and easier. I find it great for allowing management to find their own insights from raw data.

bokeh python review by Dan G.
Dan G.
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"Data science at it's finest"

What do you like best?

Bokeh is a phenomenal visualization library in Python. As a data scientist, you're constantly looking for ways to express data in more understandable manner and Bokeh lets you do just that.

What do you dislike?

I think what I dislike about this library is the learning curve. It's not easy to learn each new function and takes time.

Recommendations to others considering the product

Bokeh is a library that every business should learn to use and strive to understand so they can improve their data science skills.

What business problems are you solving with the product? What benefits have you realized?

Bokeh lets me and our team of data scientists better visualize data and know exactly what's going on with ever-growing datasets.

bokeh python review by Miriam C.
Miriam C.
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Business partner of the vendor or vendor's competitor, not included in G2 scores.

"bokeh python"

What do you like best?

Using html and javascripts for your graphics, allows you to more easily visualize the data to understand and transform for decision making, you can organize and add interactivity. and what I like the most is that its base is python speed and scalability. You can edit the code and adapt it to your needs. Easy to use and install.

What do you dislike?

It is not widely used worldwide. It is not available in other languages.

Recommendations to others considering the product

use ir, ease of use.

What business problems are you solving with the product? What benefits have you realized?

Generation of graphs for staff statistics or the company in general.

bokeh python review by Bisma B.
Bisma B.
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"Bokeh library for visualization "

What do you like best?

The library has a lot of potential to create a rainbow of visualizations. I like that the dashboards are interactive.

What do you dislike?

The help resources or learning resources are limited.

What business problems are you solving with the product? What benefits have you realized?

Creating BI dashboards. Benefits are customization because bokeh is used with python which makes it highly customizable

bokeh python review by User
User
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"Good viz library"

What do you like best?

Easy to learn and use, good for basic interactive charts. Allows you to provide charts in many mediums (html, notebook and server). Good alternative to plotly and pygal.

What do you dislike?

Plotly offers a much greater level of interactivity than bokeh out of the box.

bokeh has a problem with its documentation.

What business problems are you solving with the product? What benefits have you realized?

Data vizualization

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